A teacher using AI for lesson plans and just letting it slip in lies without checking is more nefarious because now we have the possibility of not seeing the effect of that for a decade.

My kid got a social studies review sheet that said that Mount Everest is in the city of Nepal. And yes, we know that teacher uses AI for their lesson plans.

Personally, I've had a pretty positive experience with the coding assistants, but I had to spend some time to develop intuition for the types of tasks they're likely to do well. Like if you need to crap out a UI based on a JSON payload, make a service call, add a server endpoint, LLMs will typically do this correctly in one shot. These are common operations that are easily extrapolated from their training data. Where they tend to fail are tasks like business logic which have specific requirements that aren't easily generalized.

I've also found that writing the scaffolding for the code yourself really helps focus the agent. I'll typically add stubs for the functions I want, and create overall code structure, then have the agent fill the blanks. I've found this is a really effective approach for preventing the agent from going off into the weeds.

I also find that if it doesn't get things right on the first shot, the chances are it's not going to fix the underlying problems. It tends to just add kludges on top to address the problems you tell it about. If it didn't get it mostly right at the start, then it's better to just do it yourself.

All that said, I find enjoyment is an important aspect as well and shouldn't be dismissed. If you're less productive, but you enjoy the process more, then I see that as a net positive. If all LLMs accomplish is to make development more fun, that's a good thing.